Update section title

docs/papers/paper.md

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 xCDAT (Xarray Climate Data Analysis Tools) is an open-source Python package that extends Xarray [@Hoyer:2017] for climate data analysis on structured grids. xCDAT streamlines analysis of climate and weather data by exposing common climate and weather analysis operations through a set of straightforward APIs. Some of xCDAT's key features include spatial averaging, temporal averaging, and regridding. These features are inspired by the Community Data Analysis Tools (CDAT) library [@Williams:2009] [@Williams:2017] [@Doutriaux:2017] and leverage powerful packages in the [Xarray](https://docs.xarray.dev/en/stable/) ecosystem including [xESMF](https://github.com/pangeo-data/xESMF) [@xesmf], [xgcm](https://xgcm.readthedocs.io/en/latest/) [@xgcm], and [CF xarray](https://cf-xarray.readthedocs.io/en/latest/) [@cf-xarray]. To ensure general compatibility across various climate models, xCDAT operates on datasets compliant with the Climate and Forecast (CF) metadata conventions [@Hassell:2017].
 
-# Statement of need
+# Statement of Need
 
 Analysis of climate and weather data frequently requires a number of core operations, including reading and writing of netCDF files, horizontal and vertical regridding, and spatial and temporal averaging. While many individual software packages address these needs in a variety of computational languages, CDAT stands out because it provides these essential operations via open-source, interoperable Python packages. Since CDAT's inception, the volume of climate and weather data has grown substantially as the number of data products and their spatiotemporal resolution increases. Larger data stores are important for advancing geoscientific understanding, but also require increasingly performant software and hardware. These factors have sparked a need for new analysis software that offers core geospatial analysis functionalities capable of efficiently handling large datasets while using modern technologies and standardized software engineering principles.